1

Machine Learning Engineer Quantization Jobs in Massachusetts

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact.

Machine Learning Engineer (Malden)

Malden, MA ยท On-site

$130K - $215K/yr

Base pay range $130,000.00/yr - $215,000.00/yr Direct message the job poster from Alsym Energy Alsym Energy is seeking a Machine Learning Scientist or Engineer to design, build, and deploy agentic AI ...

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact.

Lead Machine Learning Engineer

Cambridge, MA ยท On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class ...

Lead Machine Learning Engineer

Cambridge, MA ยท On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating responsible and reliable AI-powered systems. Our investments in technology infrastructure and world-class ...

Machine Learning Engineer II

Cambridge, MA ยท On-site

$106K - $145K/yr

We are seeking a mid-level Machine Learning Engineer to join our team and help shape the future of Agentic AI systems. This is a hands-on, full-lifecycle (from experimentation to productionization ...

Senior Machine Learning Engineer

Boston, MA ยท On-site

$170K - $205K/yr

About the position: We're looking for a Senior Machine Learning Engineer with deep expertise in some area of ML engineering to join our growing ML team and work closely with our software and computer ...

Showing results 41-60

Machine Learning Engineer Quantization information

What does a machine learning engineer quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What are some common challenges machine learning engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

What are the key skills and qualifications needed to thrive as a machine learning engineer quantization, and why are they important?

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What is the difference between Machine Learning Engineer Quantization vs Data Scientist?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What cities in Massachusetts are hiring for Machine Learning Engineer Quantization jobs?

Cities in Massachusetts with the most Machine Learning Engineer Quantization job openings:

Infographic showing various Machine Learning Engineer Quantization job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Senior Software Engineer

Akamai Technologies GmbH

Cambridge, MA โ€ข On-site

$150 - $200/hr

Other

Medical, Retirement, PTO

Posted 20 days ago


Job description

Machine Learning Senior Software Engineer

United States (Remote)

Job Description

Do you want to shape how AI models are validated, optimized, and deployed at global scale?

Are you passionate about building the systems that ensure AI models perform reliably and responsibly in production

Join the Akamai Inference Cloud Team!

The Akamai Inference Cloud (AIC) team is part of Akamai's Cloud Technology Group. We design and operate AI platforms enabling customers to run models with unmatched performance, compliance, and economics. This team owns the end-to-end model lifecyclefrom validation and security scanning through quantization, optimization, and monitoring. We ensure every model meets rigorous standards for quality, safety, and performance.

Partner with the best

As an ML Senior Software Engineer, you will build and operate systems responsible for model validation, quantization, and safety across the AIC. You'll develop pipelines that scan models for vulnerabilities, apply quantization and optimization techniques, and build guardrails that enforce safety and compliance policies. This role requires handsโ€‘on ML experience and deep understanding of modern architectures, inference optimization, and responsible
AI.
#AIC

As a Machine Learning Senior Software Engineer, you will be responsible for:

  • Developing and maintaining model validation and security scanning pipelines that assess models for quality, correctness, and vulnerabilities prior to deployment
  • Implementing quantization, pruning, and other optimization techniques to reduce model footprint and improve inference latency across diverse hardware
    configurations
  • Building guardrail and content safety systems that enforce compliance policies and mitigate risks such as jail breaking and prompt injection
  • Designing model routing and prompt management infrastructure that supports intelligent request handling across model variants
  • Contributing to model evaluation frameworks that measure accuracy, performance, and safety metrics across the model lifecycle

Do what you love

To be successful in this role you will:

  • Have 5 years of relevant experience and a Bachelor's/Master's degree in Computer Science, Machine Learning, or a related field
  • Demonstrate handsโ€‘on experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX, including model training, fineโ€‘tuning, and inference optimization
  • Show proficiency in model quantization techniques (GPTQ, AWQ, GGUF) and an understanding of how model compression impacts accuracy and latency
  • Have experience working with large language models (LLMs), transformer architectures, and multiโ€‘modal AI systems
  • Demonstrate familiarity with model safety and responsible AI practices, including content filtering, redโ€‘team. or adversarial robustness evaluation
  • Show proficiency in Python and experience building production data or ML pipelines
  • Have experience with containerized deployments, CI/CD practices, and cloud infrastructure (not required, but suggested)

Work in a way that works for you

FlexBase, Akamai's Global Flexible Working Program, is based on the principles that are helping us create the best workplace in the world. When our colleagues said that flexible working was important to them, we listened. We also know flexible working is important to many of the incredible people considering joining Akamai. FlexBase, gives 95% of employees the choice to work from their home, their office, or both (in the country advertised). This permanent workplace flexibility program is consistent and fair globally, to help us find incredible talent, virtually anywhere. We are happy to discuss working options for this role and encourage you to speak with your recruiter in more detail when you apply. Learn what makes Akamai a great place to work

Connect with us on social and see what life at Akamai is like!

We power and protect life online, by solving the toughest challenges, together.

At Akamai, we're curious, innovative, collaborative and tenacious. We celebrate diversity of thought and we hold an unwavering belief that we can make a meaningful difference. Our teams use their global perspectives to put customers at the forefront of everything they do, so if you are people-centric, you'll thrive here.

Working for you

At Akamai, we will provide you with opportunities to grow, flourish, and achieve great things. Our benefit options are designed to meet your individual needs for today and in the future. We provide benefits surrounding all aspects of your life:

  • Your health
  • Your finances
  • Your family
  • Your time at work
  • Your time pursuing other endeavors

Our benefit plan options are designed to meet your individual needs and budget, both today and in the future.

About us

Akamai powers and protects life online. Leading companies worldwide choose Akamai to build, deliver, and secure their digital experiences helping billions of people live, work, and play every day. With the world's most distributed compute platform from cloud to edge we make it easy for customers to develop and run applications, while we keep experiences closer to users and threats farther away.

Are you seeking an opportunity to make a real difference in a company with a global reach and exciting services and clients? Come join us and grow with a team of people who will energize and inspire you! Akamai Technologies is an Affir... | All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of gender, gender identity, sexual orientation, race/ethnicity, protected veteran status, disability, or other protected group status. If no date is displayed, applications are being accepted on an ongoing basis until the job is filled.

Compensation

Akamai is committed to fair and equitable compensation practices. For US based candidates only - the base salary for this position ranges from $121,400 - $218,600/year; a candidateโ€™s salary is determined by various factors including, but not limited to, relevant work experience, skills, certifications and location. Compensation for candidates outside the US will vary. The compensation package may also include incentive compensation opportunities in the form of annual bonus or incentives, equity awards and an Employee Stock Purchase Plan (ESPP). Akamai provides industry-leading benefits including healthcare, 401K savings plan, company holidays, vacation (in the form of PTO), sick time, family friendly benefits including parental leave and an employee assistance program including a focus on mental and financial wellness; Eligibility requirements apply.

Job Info
  • Job Identification 2647
  • Posting Date 08/05/2026, 10:21 PM
  • Locations 145 Broadway, Cambridge, MA, 02142, US (Remote)
#J-18808-Ljbffr